氮化硅结合碳化硅材料反应烧结时的杂质相行为分析

分析了Ｓｉ３Ｎ４结合ＳｉＣ材料反应烧结时Ｆｅ２Ｏ３，ＳｉＯ２，Ａｌ２Ｏ３，ＣａＯ等杂质相的反应行为。     

以TCaCO3／TSiO2监控生料KH

以Ｔ_（ＣａＣＯ）_３／Ｔ_（ＳｉＯ）_２监控生料ＫＨ冯正武陕西省南郑县水泥厂（７２３１０１）１引言在质量控制中，水泥厂一般用控制ＴＣａＣＯ３、ＴＦｅ２Ｏ３两项指标来稳定配料。而ＣａＣＯ３、Ｆｅ２Ｏ３合格率只是一种代用质量特性，真正质量特性是率值（ＫＨ、...     

助剂对铁系CO变换催化剂结构和稳定性影响的X-射线衍射研究

采用Ｘ－射线衍射法（ＸＲＤ） 测定加入助剂Ｃｒ２Ｏ３、Ｂｉ２Ｏ３、ＣｅＯ２ 的γ－Ｆｅ２Ｏ３ 催化剂还原前后的物相及氧化铁晶胞参数和晶粒度, 结果表明, Ｃｒ２Ｏ３、Ｂｉ２Ｏ３、ＣｅＯ２ 都没有取代Ｆｅ２Ｏ３ 晶胞中的铁原子, 但它们在催化剂中的作用是不同的。Ｃｒ２Ｏ３ 和Ｂｉ２Ｏ３ 进入Ｆｅ２Ｏ３ 的晶格中, 能抑制氧化铁晶粒的长大, 提高了催化剂的活性和稳定性; 而ＣｅＯ２ 则堆积在氧化铁表面, 它对氧化铁晶粒的长大作用不大, 它使催化剂活性大大提高必定有其它因素起作用。     

外加剂对磷石膏还原性分解过程的影响

采用非等温热重法在３０－１２００℃内研究了外加剂（ＳｉＯ２,Ｆｅ２Ｏ３,ＣａＣｌ２,ＣａＯ,ＮａＣｌ,Ｎａ２ＳｉＦ６,Ｎａ２ＣＯ３）在含３％的还原性气体介质中对磷石膏及其配合料的热分解过程的影响。试验结果表明,ＣａＣｌ２,Ｆｅ２Ｏ３和Ｓｉｏ２及其复合型外加剂促进了分解过程,可降低分解温度和提高分解艇较显著,可供进一步优选加速磷石膏及其配合料热分解过程的外加剂参数。     

助剂对铁系CO变换催化剂结构和稳定性影响的X—射线衍射研究

采用Ｘ－射线衍射法测定加入助剂Ｃｒ２Ｏ３,Ｂｉ２Ｏ３,ＣｅＯ２的γ－Ｆｅ２Ｏ３催化剂还原前后的物相及氧化铁晶胞参数和晶粒度,结果表明,Ｃｒ２Ｏ３,Ｂｉ２Ｏ３,ＣｅＯ２都没有取代Ｆｅ２Ｏ３晶胞中的铁原子,但它们在催化剂中的作用是不同的。Ｃｒ２Ｏ３和Ｂｉ２Ｏ３进入Ｆｅ２Ｏ３的晶格中,能抑制氧化铁晶粒的长大,提高了催化剂活性和稳定性;     

混合负载型双金属簇催化剂的CO加氢反应

本文制备了两种类型的双金属簇催化剂［Ｆｅ·ＣＯ＿３·Ｃｕ·ＡＬ＿２Ｏ＿３］和［ＫＣＯＦｅ＿３．ＳｉＯ＿２］，评价了其在ＣＯ加氢反应中的催化性能，并考察了混合的双金属簇催化剂对ＣＯ加氢反应催化活性和选择性的影响。     

快速测定生料CaO,SiO2监控生料KH

快速测定生料ＣａＯ、ＳｉＯ＿２监控生料ＫＨ陆海涛江苏盐城建湖水泥厂（２２４７００）我厂原以出磨生料ＴＣａＣＯ３及ＴＦｅ２Ｏ３合格率来监控生料ＫＨ，在控制过程中，即使出磨生料ＴＣａＣＯ３、ＴＦｅ２Ｏ３合格率较高，但仍得不到合格的ＫＨ，原因是包括我厂在内...     

含炭耐火材料添加Al4SiC4的作用

Ａｌ４ＳｉＣ４是一种极好的抗水化化合物，它作为含炭耐火材料的抗氧化剂，对其性能用作用进行了研究，并探讨了相应机理。Ａｌ４ＳｉＣ４添加到含炭耐火材料中，起初与ＣＯ反应，生成Ａｌ２Ｏ３、ＳｉＣ和Ｃｏ反应后，如果温度在－１５６０℃以下，生成的ＳｉＣ和Ａｌ２Ｏｅ将进一步与ＣＯ应生成莫来石（Ａｌ６ＳｉＣ２Ｏ１３）和Ｃｏ。在耐火材料表面进行的上述反应形成了保护层，这就阻止了耐火材料的氧化。为此，Ａｌ４ＳｉＣ４     

烧结MgO在SiO2—FeO—CaO与FeS—Cu2S熔体界面区的局部侵蚀

采用坩埚法，借助自行设计的高温Ｘ射线透射影视设备，通过Ｘ射线照像主电视观察，研究了烧结ＭｇＯ材料在炉渣（ＳｉＯ２－ＦｅＯ－ＣａＯ）与冰铜（ＦｅＳ－Ｃｕ２Ｓ）界面区局部优先侵蚀过程。发现：ＭｇＯ材料在渣中ＦｅＯ形成致密的（Ｆｅ，Ｍｇ）Ｏ层，紧邻（Ｆｅ，Ｍｇ）Ｏ层形成渣膜，而界面张力流的存在使渣膜产生运动，促进渣膜层中ＭｇＯ的传质过程，加速ＭｇＯ材料的侵蚀，从而引起ＭｇＯ材料在渣－冰铜界面区局部优先侵     

酞菁铜-Fe3O4纳米复合粒子复合机理及其性能的研究

制备了酞菁铜（ＣｕＰｃ）－Ｆｅ３Ｏ４纳米复合粒子,分析了ＣｕＰｃ与Ｆｅ３Ｏ４纳米粒子的复合过程,提出了其复合机理。研究并建立了ＣｕＰｃ－Ｆｅ３Ｏ４纳米复合粒子的结构模型,研究了复合粒子的抗氧化性和热性。结果表明,ＣｕＰｃ与Ｆｅ３Ｏ４纳米粒子之间形成了化学键。在复合过程中,首先一部分ＣｕＰｃ与Ｆｅ３Ｏ４纳米粒子表面的氧离子形成化学键;然后Ｆｅ３Ｏ４纳米粒子发生聚集,形成聚集体;最后相当一部分ＣｕＰＣ     

Stochastic Modelling of Grain Moisture Content.in Near-Ambient Drying

A stochastic analytical model was developed to describe the mass transfer in a thin layer of grain ventilated with unheated air. As an excitation to the drying system, a stochastic analytical model of variations in ambient air temperature and relative humidity during the drying period, based on a sine function. was used. Mean. carrelation function, variance and the standard deviation were determined for main moisture content treated as a random process. The stochastic models of variations in air temperature and relative humidity were fined to the observed historical data. The standard deviation and m ean of grain moisture content calculated from the developed analytical model were compared to changes in mean and the standard deviation obtained from the numerical deterministic model of mass transfer and hourly weather data from 17 year.     

Optimal discrete stochastic control theory for process application

The design of discrete feedback controllers which minimize some linear function of the variances of the output deviations from target subject to possible constraints on the variances of the inputs, for linear systems subject to stochastic disturbances, is treated from two points of view: (1) using transfer function models to characterizing the process dynamics and autoregres-sive-moving-average models to characterize the stochastic disturbances, and then solving the optimal control problem using an approach due to Box and Jenkins and a discrete version of the Wiener-Newton theory; and (2) using state variable models to characterize both the dynamic and stochastic parts of the system, and then solving the optimal control problem using the results of dynamic programming and Kalman filtering. Practical considerations such as model forms, their identification and estimation, and the development of variance relationships that are necessary for the application of these two approaches in the process industries are discussed. The relationship between and a comparison of these two approaches is made.     

Stochastic Modelling of Grain Moisture Content.in Near-Ambient Drying

ABSTRACT

A stochastic analytical model was developed to describe the mass transfer in a thin layer of grain ventilated with unheated air. As an excitation to the drying system, a stochastic analytical model of variations in ambient air temperature and relative humidity during the drying period, based on a sine function. was used. Mean. carrelation function, variance and the standard deviation were determined for main moisture content treated as a random process. The stochastic models of variations in air temperature and relative humidity were fined to the observed historical data. The standard deviation and m ean of grain moisture content calculated from the developed analytical model were compared to changes in mean and the standard deviation obtained from the numerical deterministic model of mass transfer and hourly weather data from 17 year.     

Modelling of fluidized bed reactors—VI(b): The nonisothermal bed with stochastic bubbles

Two stochastic nonisothermal fluidized bed reactor models are developed to investigate the significance of the fluctuating nature of fluidized beds on reactor performance. Fluctuating bubble size distributions within the bed are simulated by stochastic mass and heat transfer coefficients. Results of hybrid computer simulations indicate that randomness can enhance or inhibit reactor performance depending on the operating parameters of the nonisothermal model. Bubble and dense phase concentration statistics are fairly similar to those of corresponding isothermal models because dense phase temperatures are relatively insensitive to transfer coefficient fluctuations due to the high dense phase beat capacity. However, the corresponding stochastic isothermal models predict decreases in conversion with increasing variance in the transfer coefficients for all operating conditions. Results indicate that a deterministic system with two stable steady states may have fewer stable random stationary solutions. The existence of the stationary states is dependent on fluctuation frequency and variance of the transfer coefficients.     

THE PREDICTIVE PERFORMANCE OF THREE AUTOREGRESSIVE MOVING-AVERAGE MODELS:A MONTE CARLO INVESTIGATION

Abstract. The relative accuracy of point and interval forecasts from three related autoregressive moving-average (ARMA) models—multivariate, univariate, and transfer function—is evaluated in this study. It is found that the multivariate models produce the most accurate one- and three-step-ahead point forecasts of nonindependent series. However, the most accurate point forecasts of independent series are generated by the univariate models. Compared with the multivariate models, the transfer function predictions are relatively unreliable, but with the appropriate restrictions they are superior to the univariate forecasts in certain cases. Interval forecasts from the correctly specified models are reliable indicators of forecast dispersion.     

微波消解法测定水中高锰酸盐指数的最佳条件

讨论了微波消解功率、消解时间、酸度等条件对测定水样中的高锰酸盐指数分析结果的影响,建立起来了利用微波消解法快速测定水中高锰酸盐指数的最佳试验条件,并测定了该方法抗Cl-干扰的能力、精密度及准确度,为利用该方法测定水样中的高锰酸盐指数提供了依据。     

A Note on the Filtering for Some Time Series Models

Abstract.  This paper is concerned with filtering for various types of time series models including the class of generalized ARCH models and stochastic volatility models. We extend the results of Thavaneswaran and Abraham (1988) for some time series models using martingale estimating functions. Nonlinear filtering for biostatistical time series models with censored observations is also discussed as a special case.     

相转移催化氧化法合成硝基苯甲酸

研究了季铵盐 A- 1催化高锰酸钾氧化邻、对硝基甲苯 ,合成邻、对硝基苯甲酸的反应。考察了不同相转移催化剂的催化活性 ,催化剂用量、反应温度、反应时间、KMn O4 用量和反应体系酸碱性对反应的影响。在优化反应条件 ,即以季铵盐 A- 1为相转移催化剂 ,高锰酸钾与硝基甲苯摩尔比为 2 .5∶ 1 ,反应温度为 95°C,反应时间为 3h,在中性条件下进行反应 ,邻位、对位产物收率分别可达 95 %、92 %。实验表明 ,季铵盐 A- 1对于高锰酸钾氧化硝基甲苯合成硝基苯甲酸的反应 ,是一种优良的相转移催化剂     

A study in injection molding dynamics

Some aspects of injection-molding dynamics were studied using a laboratory injection-molding machine operated under the control of a microprocessor-based servocontrol system. Two types of experiments were performed: deterministic tests which introduced step changes in the servovalve opening and stochastic tests using pseudo-random binary sequence (PRBS) perturbations of the servovalve. Deterministic models were written for the hydraulic and nozzle pressures which were in good agreement with the experimental data. A stochastic transfer function-noise model was obtained for the nozzle pressure, but an adequate model was not found for the hydraulic pressure. The agreement between the nozzle pressure stochastic model and the corresponding step test model was satisfactory.